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Magnetic checkerboard separates microparticles by size and sends them along different paths

A team of researchers from the Universities of Tübingen, Bayreuth, and Kassel, and the Polish Academy of Sciences has developed a method for precisely controlling the movement of magnetic microparticles based on their size. These suspended particles, known as colloidal particles, range in size from a few tens of nanometers to several micrometers. Controlling them is important for applications such as drug delivery, medical laboratory tests, and the synthesis of new materials. The team’s study has now been published in Physical Review Letters.

The new method involves positioning microparticles above a magnetic layer that is patterned like a chessboard. In previous studies, magnetic transportation of the colloidal particles was limited to a specific height. At this distance, although the magnetic forces appear to balance each other out, the particles move regardless of their size. Therefore, it was not possible to control the particles specifically based on their size.

Mobile qubits on a chip move us a step closer to everyday quantum computers

For years, quantum computers have lived under a huge bubble of hype, promising to revolutionize numerous fields, from medicine and battery design to materials science and cybersecurity. But realizing their potential on any serious practical level will only be possible if large numbers of qubits (the basic units of information) can interact with each other with high precision and flexibility.

One of the main things holding that back is that traditional qubits are fixed in place, meaning they can only talk to their immediate neighbors. But in a new paper published in Nature, scientists describe how they overcame this limitation by using mobile qubits that can be moved around a chip. Lars R. Schreiber at the JARA-FIT Institute for Quantum Information in Germany has also published a News & Views piece in the same journal.

Testing quantum collapse theory with the XENONnT dark matter detector

Theories of quantum mechanics predict that some particles can exist in superpositions, which essentially means that they can be in more than one state at once. When a particle’s state is measured, however, this superposition appears to “collapse” into a single outcome; a phenomenon often referred to as the “measurement problem.”

In recent years, various theoretical physicists have tried to explain why and how this collapse happens. This led to the introduction of various models, such as the Continuous Spontaneous Localization (CSL) and Diósi–Penrose models.

Both these models predict that spontaneous quantum collapse would also lead to the emission of faint X-ray radiation. The experimental detection of this radiation would thus provide evidence of these theories’ validity.

AI tool unifies fragmented cell maps into spatial atlases across tissues

A new computational method could dramatically accelerate efforts to map the body’s cells in space, according to a study published in Nature Genetics. Spatial multi-omics technologies—often described as ultra-high-resolution maps of tissues—allow scientists to see not only which genes or proteins are active in a cell, but exactly where that activity occurs. That spatial context is critical for understanding complex organs such as the brain, immune tissues and developing embryos.

Unfortunately, capturing multiple molecular layers at once remains expensive and technically challenging, said David Gate, Ph.D., assistant professor in the Ken and Ruth Davee Department of Neurology’s Division of Behavioral Neurology, who was a co-author of the study.

“In practice, investigators end up with ‘mosaic’ datasets: different slices or batches that each capture only some of the layers, often from different technologies or labs, with batch effects and missing pieces,” said Gate, who also leads the Abrams Research Center on Neurogenomics.

3D-MIND: A flexible device that can be integrated with living brain cells

Contemporary artificial intelligence (AI) systems, such as the models underpinning the functioning of ChatGPT, image generators and AI-powered creative tools, draw inspiration from the human brain’s functions and organization. While many of these systems are known to perform remarkably well on specific tasks, they still work independently from the human brain.

Researchers at Princeton University set out to create a flexible electronic system that could be directly embedded with groups of living brain cells to create a hybrid biocomputing platform. The new hybrid device they developed, dubbed 3D-MIND, was introduced in a paper published in Nature Electronics.

“This work started with a growing challenge in modern AI,” Tian-Ming Fu, senior author of the paper, told Tech Xplore. “Today’s systems can do incredible things, but they consume enormous amounts of energy, so much that their power demand is starting to shape real-world infrastructure and raise environmental concerns.

Inspired by the brain, researchers build smarter and more efficient computer hardware

As traditional computer chips reach their physical limits and artificial intelligence demands more energy than ever, University of Missouri researchers are rethinking how computers work by taking cues from the human brain. The timing is critical. Energy use from AI data centers is projected to double by the end of the decade, raising urgent questions about sustainability.

The solution may lie in neuromorphic computing, an approach that reimagines computer hardware to process information more like biological neural networks rather than conventional chips.

“One of the brain’s greatest advantages is its efficiency,” Suchi Guha, a professor of physics in Mizzou’s College of Arts and Science, said. “It performs incredibly complex tasks using about 20 watts of power—roughly the same as an old light bulb. By comparison, today’s computer architecture is extremely energy-intensive.”

Quantum metallurgy: Electron crystals deform and melt

In a process analogous to how solids melt into liquids, the electrons in many different metals form crystal-like patterns that can deform and melt, opening new pathways for neuromorphic computing and superconductors, University of Michigan Engineering researchers have found.

“Our work shows that these quantum structures, which are often thought to have a highly ordered structure, actually span a continuum of disorder that could be leveraged to engineer and control these materials,” said Robert Hovden, associate professor of materials science and engineering and corresponding author of the study published in Matter.

“Metallurgists often control defects, or disorder, in metals to produce specific properties,” Hovden said. “A similar approach might help us harness the potential of quantum materials in future devices. Quantum metallurgy could be the future.”

Focused helium ions create ferroelectric regions in aluminum nitride for lower-power chips

Scientists at the Department of Energy’s Oak Ridge National Laboratory have shown for the first time that ferroelectricity can be directly written into aluminum nitride using a tightly focused helium ion beam at the Center for Nanophase Materials Sciences (CNMS), a DOE Office of Science user facility at ORNL. Ferroelectric devices don’t need constant power to store data, which allows for devices that are more reliable and less power consuming than what’s currently available.

The study, published in Advanced Materials, represents a new processing approach for wurtzite III-V nitrides, a class of semiconductors already widely used in microelectronics but whose ferroelectric potential has only been recognized since 2019.

“Today, both the material and the processing method are already employed in chip manufacturing: aluminum nitride is widely used in many 5G and Wi-Fi devices, and helium ion beams are common tools to make tiny changes to circuits,” said Bogdan Dryzhakov, an ORNL postdoctoral research associate at CNMS.

Researchers combine five metals to build a better nanocrystal

A nanocrystal is an extraordinarily tiny piece of material—composed of anywhere from a few to a few thousand atoms—in which atoms are arranged in a precise, ordered structure. Think of it like taking a piece of gold and shrinking it down to the size of a few hundred atoms. It’s still gold, still crystalline, just almost incomprehensibly small.

Nanocrystals are in the transistors inside computers and smartphones, in smartphone displays and TV screens, in the gold-nanoparticle sensors that power COVID and pregnancy tests, and in the pipes of your car exhaust system, among countless other innovations.

Their small size gives them a dramatically higher ratio of surface area to volume, making them especially useful as catalysts—materials that speed up chemical reactions without being consumed in the process.

Harmless viruses trap Salmonella on flexible polymer in portable microfluidic sensor

Researchers at Worcester Polytechnic Institute (WPI) have developed a solid polymer coated with harmless viruses to detect the bacteria Salmonella enterica (S. enterica), an advance that could lead to new ways of finding contamination in the food supply. The work is published in the journal ACS Applied Bio Materials.

The group, led by Yuxiang “Shawn” Liu, an associate professor in the Department of Mechanical and Materials Engineering, reports that the technology can rapidly capture and visualize foodborne bacterial contaminants in tiny fluid samples. With no need for incubation or complicated equipment in research centers, the technology has the potential to be used as a rapid biosensor in field applications and in areas with few resources.

“We have a solid surface that can be used anywhere in the food supply chain, from farm to fridge, to detect foodborne bacteria with minimum human intervention,” Liu says.

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